Since the late 1980s, a series of Plasmodium falciparum malaria epidemics have occurred in the highlands of African countries. The current pattern of malaria in the highlands exhibits the characteristics of an expanded geographic area, increased frequency, and increased fatality rates. What has caused the more frequent and more widespread malaria epidemics since the late 1980s in African highlands? Can we forecast when and where an epidemic will occur so that appropriate actions can be taken in advance to reduce morbidity and mortality? How can we maximize the efficacy and cost-effectiveness of vector control to reduce malaria transmission and incidence in the highlands? These questions are not only of scientific interest, but they are also of paramount importance for malaria control. The long-term objectives of this research are to determine the mechanisms of malaria epidemics in African highlands, and to develop efficient vector control methods for epidemic malaria control. In the previous period of support, we made significant progress elucidating the effects of land use and land cover on malaria transmission in African highlands. We proposed the climate-landscape hypothesis as a leading mechanism for the emergence of epidemic malaria in African highlands. This competing renewal application will test the climate-landscape hypothesis using epidemiological, entomological, and molecular population genetics data in western Kenya highlands. The proposed research has three specific aims. First, we will determine the impact of climate factors on malaria incidence and test the accuracy and sensitivity of using weather anomalies for future malaria epidemic forecasting. Second, we will determine the effects of landscape (topography, land use, and land cover) on the spread of malaria infections. Third, we will assess the impact of mosquito vector control targeted at transmission hotspots on rates of malaria transmission, infection incidence, and clinical malaria occurrence. This project will achieve the following goals: a) reveal critical parameters needed for the development of malaria early warning systems in African highlands, b) significantly enhance our understanding of the relationships between climate, landscape, and the transmission dynamics of malaria, and c) facilitate the development of cost-effective malaria vector control methods. We anticipate that our results will have broad applicability to malaria prevention and control in Africa.